Merck Ad5/HIV induces broad innate immuneactivation that predicts CD8+ T-cell responses butis attenuated by preexisting Ad5 immunityDaniel E. Zaka,1, Erica Andersen-Nissenb,1, Eric R. Petersonb, Alicia Satob, M. Kristina Hamiltona, Joleen Borgerdingb,Akshay T. Krishnamurtyb, Joanne T. Changb, Devin J. Adamsb, Tiffany R. Hensleyb, Alexander I. Salterb,Cecilia A. Morganb,c, Ann C. Duerrb,c, Stephen C. De Rosab,c,d, Alan Aderema,e,2,3, and M. Juliana McElrathb,c,f,2,3

aSeattle Biomedical Research Institute, Seattle, WA 98109; bVaccine and Infectious Disease Division and cHIV Vaccine Trials Network, Fred Hutchinson CancerResearch Center, Seattle, WA 98109; and dDepartment of Laboratory Medicine, eDepartment of Immunology, and fDepartment of Medicine, University ofWashington, Seattle, WA 98195

Edited* by Rafi Ahmed, Emory University, Atlanta, GA, and approved October 16, 2012 (received for review June 5, 2012)

To better understand how innate immune responses to vaccinationcan lead to lasting protective immunity, we used a systems ap-proach to define immune signatures in humans over 1 wk followingMRKAd5/HIV vaccination that predicted subsequent HIV-specific T-cell responses. Within 24 h, striking increases in peripheral bloodmononuclear cell gene expression associated with inflammation,IFN response, and myeloid cell trafficking occurred, and lympho-cyte-specific transcripts decreased. These alterations were corrobo-rated by marked serum inflammatory cytokine elevations andegress of circulating lymphocytes. Responses of vaccinees with pre-existing adenovirus serotype 5 (Ad5) neutralizing antibodies werestrongly attenuated, suggesting that enhanced HIV acquisition inAd5-seropositive subgroups in the Step Studymay relate to the lackof appropriate innate activation rather than to increased systemicimmune activation. Importantly, patterns of chemoattractant cyto-kine responses at 24 h and alterations in 209 peripheral bloodmono-nuclear cell transcripts at 72 h were predictive of subsequent in-duction and magnitude of HIV-specific CD8+ T-cell responses. Thissystems approach provides a framework to compare innate re-sponses induced by vectors, as shown here by contrasting the morerapid, robust response to MRKAd5/HIV with that to yellow fevervaccine. When applied iteratively, the findings may permit selectionof HIV vaccine candidates eliciting innate immune response profilesmore likely to drive HIV protective immunity.

immunology | innate immunity | systems biology | systems vaccinology |immunogenicity

Ahighly efficacious HIV vaccine offers the greatest promise tohalt theHIV pandemic. Results of the RV144 study conducted

in Thailand, where a canarypox vector prime and subunit proteinboost regimen showed 31% efficacy for reducing HIV-1 acquisition(1), have given hope that development of a successful HIV vaccineis possible, and suggest that the vector prime is important forshaping a protective response. Innate immune responses direct theadaptive immune response and thus influence the potential for in-ducing long-lived protective immunity (2). A comprehensive un-derstanding of the molecular programs underlying optimal innateresponses would therefore facilitate enhanced vaccine design. Littleis known at present about the innate immune responses induced bycandidate HIV vaccines, how these responses drive adaptive im-munity, and how these innate responses compare with those in-duced by licensed efficacious vaccines against other pathogens.To begin tofill these gaps in our knowledge, we conducted a phase

Ib clinical trial (HVTN 071) to analyze, at the systems level, humaninnate immune responses to the replication-incompetent Merckadenovirus serotype 5 vaccine vector containing HIV-1 inserts gag/pol/nef (MRKAd5/HIV), in parallel with two phase IIb efficacy trialsbeing conducted using the same vaccine. Although this vaccine didnot offer protection fromHIV acquisition or lower viral loads in thephase IIb Step or Phambili studies (HVTN 502 and 503), it elicitedhigh CD8+ T-cell response rates to the HIV-1 inserts (3–5), and

recent sieve analyses provide evidence that vaccine responses exertedselective pressure on infecting HIV-1 strains (6). The MRKAd5/HIV vaccine received particular attention when the Step Studyanalysis revealed that certain vaccine subgroups with baseline Ad5seropositivity exhibited increased HIV-1 acquisition rates, haltingits further use in all HIV-1 vaccine trials involving Ad5 seroposi-tive subjects. Although hypotheses have been generated that mayexplain vaccine-induced increased HIV-1 infection rates (3, 7, 8)and enhanced acquisition was recently recapitulated in the simianimmunovirus (SIV) challenge model (9), no clear mechanismshave been identified to date. These findings, coupled with theimportance of the Ad5 and other adenovirus serotype vectors tovaccine development against many other pathogens (10, 11),reinforced our motivation to use an unbiased systems biologyapproach to better understand the innate immune response trig-gered by MRKAd5/HIV.Systems biology integrates global molecular measurements and

computational analysis with prior knowledge to generate holisticbiological insights. This approach therefore provides a frameworkto address complex vaccine-induced immunological responses(12, 13). Crosstalk and feedback can be elucidated between im-mune signaling pathways and gene regulatory networks operatingon multiple spatial and temporal scales. We have previously ap-plied systems analysis to identify gene and signaling networks thatcoordinately amplify and attenuate Toll-like receptor (TLR)-mediated responses underlying innate immune cell activation(14–17). Recent systems analyses of responses to vaccination withthe highly efficacious YF-17D yellow fever vaccine (18, 19) andseasonal influenza vaccine (20) have yielded novel insights abouttheir mechanisms of action. Building on this systems-level ap-proach, we describe here the innate immune responses induced byMRKAd5/HIV, how they are impacted by preexisting Ad5 neu-tralizing antibodies (nAb), how they relate to induction of T-cellresponses, and how they differ from those induced by live-attenuated YF-17D.

Author contributions: D.E.Z., E.A.-N., A.A., and M.J.M. designed research; D.E.Z., E.A.-N.,E.R.P., A.S., M.K.H., A.T.K., J.T.C., D.J.A., T.R.H., A.I.S., andM.J.M. performed research; D.E.Z.,E.A.-N., E.R.P., A.S., M.K.H., J.B., A.T.K., J.T.C., D.J.A., T.R.H., A.I.S., S.C.D., and M.J.M. ana-lyzed data; D.E.Z., E.A.-N., A.A., and M.J.M. wrote the paper; D.E.Z. performed microarraydata analysis; and C.A.M., A.C.D., and M.J.M. implemented the clinical protocol.

The authors declare no conflict of interest.

*This Direct Submission article had a prearranged editor.

Data deposition: The data reported in this paper have been deposited in the Gene Ex-pression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE22822).1D.E.Z. and E.A.-N. contributed equally to this work.2A.A. and M.J.M. contributed equally to this work.3To whom correspondence may be addressed. E-mail: alan.aderem@seattlebiomed.org orjmcelrat@fhcrc.org.

See Author Summary on page 20194 (volume 109, number 50).

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1208972109/-/DCSupplemental.

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ResultsMRKAd5/HIV Dramatically Remodels Peripheral Blood MononuclearCell Transcriptomes by Triggering Robust Innate Immune and CellTrafficking Responses. We assessed the innate immune responseto MRKAd5/HIV by profiling transcriptomes of peripheral bloodmononuclear cells (PBMC) isolated from seven Ad5 nAb sero-negative individuals (Ad5 nAb titer ≤18; Ad5Neg) during the firstweek after vaccination, by gene-level analysis of Affymetrix exonmicroarrays. Responses to MRKAd5/HIV peaked at 24 h, with1,026 genes exhibiting enhanced and 1,048 genes exhibiting re-pressed expression levels compared with prevaccination (Fig. 1Aand Dataset S1, tab 1). At 72 h postvaccination, the differentiallyexpressed genes were a small subset of those detected at 24 h(Dataset S1, tab 2). No significantly differentially expressed geneswere detected at 168 h.We used a modular analysis framework (21) to interpret the

transcriptional response. This approach deconvolutes complextranscriptional profiles into functionally interpretable patternsthrough the evaluation of combined expression responses of pre-defined disease, cell type, and stimulus-specific coexpressed genegroups. We used versions of the functional modules defined byChaussabel et al. (21, 22) that were updated throughmeta-analysisof a much larger transcriptional dataset encompassing many moredisease states (23), to annotate the differentially expressed genelists and to examine the differential expression of the overallmodules themselves. We confirmed the functional annotations ofthe gene modules themselves by performing canonical pathwayenrichment analysis (Dataset S1, tab 3). Mirroring the gene-levelresults, the modular response peaked at 24 h (13 up-regulated and11 down-regulated modules), waned by 72 h (two up-regulatedmodules), and returned to baseline by 168 h (Fig. 1B). Modulesinduced by MRKAd5/HIV were associated with cell intrinsic in-nate immune responses (“Inflammation” and “Interferon re-sponse” modules) and influx of inflammatory cells (“Myeloidlineage” module). Concomitantly, the “Lymphoid lineage,” “Tcells,” and “Cytotoxicity”modules were suppressed, leading to thehypothesis that the vaccine was stimulating an influx of myeloidcells and an efflux of lymphoid cells from the circulation. Thishypothesis was further supported by comparing the lists of up- anddown-regulated genes with published cell-type enriched gene listsgenerated from meta-analysis of a compendium of sorted celltranscriptomes (20). Thirty-two percent of the genes we detectedas up-regulated at 24 h were identified as preferentially expressedin monocytes in that study, whereas 28% of the down-regulatedgenes we detected were preferentially expressed in lymphocytes(Dataset S1, tab 1). Rapid lymphocyte trafficking in response toMRKAd5/HIV is consistent with similar observations made inprevious studies with an adenoviral-vectored vaccine (24). Directcanonical pathway enrichment analysis of the regulated gene setsprovided additional support for the module analysis results, in-dicating that innate immune pathways and cell types were up-regulated in response to vaccination, and lymphocyte cell typesand pathways were down-regulated (enrichment results andpathway figures in Dataset S1, tabs 4 and 5).We validated the microarray results at the transcript, protein,

and cellular levels. First, we quantified and confirmed the dif-ferential expression of mRNAs associated with several vaccine-regulated modules, including “Interferon response” [C-X-C motifchemokine 10 (CXCL10), ISG-15, and STAT1] (Fig. 1C). Next,we corroborated the differential expression of many cytokinesand chemokines at the protein level using multiplex serumanalyte analysis (Fig. 1D and Dataset S1, tab 6), detecting robustchanges in serum levels of IP-10, I-TAC, monocyte chemo-attractant protein-1 (MCP-1), and MCP-2, as well as immuno-regulatory IL-10 and IL-1Ra. Finally, we validated the cellulartrafficking responses predicted from the modular analysis bydirectly assessing circulating peripheral blood leukocyte con-centrations (Fig. 1E and Dataset S1, tab 7), confirming vaccine-induced influx of monocytes and pronounced efflux of lympho-cyte populations (T, B, and NK cells). Monocyte increases arelikely a result of recruitment from the bone marrow in response

to MCP-1 and other chemokines (25). Taken together, theseresults validate the robust systemic innate immune response toMRKAd5/HIV revealed by the transcriptional profiling.

The In Vivo Innate Immune Response to MRKAd5/HIV Is Recapitulatedin Vitro and Engages a Coordinately Regulated Interacting NetworkInvolving Unique Gene Isoforms. To decouple the in vivo innateresponses intrinsic to the circulating cells from those associatedwith cells trafficking into and out of the circulation, we extendedour transcriptional profiling to PBMC stimulated with the vac-cine vector in vitro. We profiled RNA from unstimulated PBMCand PBMC incubated for 24 h with MRKAd5 at a dose sufficientto induce robust cytokine responses (Fig. S1). We found that 8 of13 (62%) modules induced in vivo were also induced in vitro andthese consisted of the three “Interferon response modules” aswell as unannotated modules largely comprised of innate im-mune response genes (Fig. 2A). Remarkably, 92% concordancebetween the in vivo and in vitro induction of IFN response geneswas observed (Dataset S1, tab 8). Many of the modules discor-dant between the in vitro and in vivo responses were associatedwith particular cellular lineages (myeloid, lymphoid, T cell, Bcell) or cell-type specific attributes (cytotoxicity) (Fig. 2B), sug-gesting that the much of the discrepancy between the in vivo andin vitro responses arose from an absence of cell trafficking invitro. Comparison with cell-type specific genes lists (20) in-dicated 35% of the genes up-regulated in vivo but not in vitro arepreferentially expressed in monocytes (Dataset S1, tab 8), sup-porting this hypothesis.Our exon-level transcriptional analyses from previous studies

demonstrated that defective alternative mRNA splicing results inprofound phenotypic differences in memory T cells (26), and thatalternative exon use occurs in the innate response. We thereforeextended our analysis of theMRKAd5-induced innate response tothe exon-level to further enrich our understanding of the action ofthe vaccine, with the primary focus of identifying vaccine-regulatedgenes not already detected by the gene-level analysis, particularlythose behaving concordantly in vitro and in vivo. Exon-levelanalysis led to the identification of 94 additional vaccine-inducedgenes in vivo and in vitro (Dataset S1, tab 9), including criticalinnate immune pathway genes (TLR3, RIPK1, and NLRC5) andseveral genes with important roles in HIV infection (APOBEC3G,APOBEC3F, CCR5, and CD74). Additionally, alternative tran-scription analysis identified 16 genes with vaccine-induced re-sponses that varied strongly from exon to exon, but were nev-ertheless consistent in vitro and in vivo, includingFANCA, FARP2,RERE, GBP6, and GBP7 (Fig. 2C and Dataset S1, tab 10). Al-though the IFN-γ–induced antimicrobial GTPases GBP6 andGBP7 have been associated with immune responses, most of theother 16 genes have not been, suggesting additional leads thatcould be investigated to further understand vaccine-induced im-munological memory. Induction of the unique short isoform ofFANCA as part of the MRKAd5-induced innate immune re-sponse, for example, provides a compelling link between DNAdamage pathways and the immunogenicity of adenoviral vectors.We performed interaction network analysis to determine

whether the genes commonly regulated by MRKAd5 in vitroand in vivo constituted established pathways or representedisolated nodes. This analysis revealed a densely intercon-nected network involving multiple modules and includedgenes detected by gene-level analysis, exon-level analysis, andalternative transcription analysis [visualized using Cytoscape(27) in Fig. 2D]. These findings indicate coordinate regulationof large functional subnetworks, including viral nucleic acidsensors, innate immune adaptors, inflammasome components,and antiviral effectors.

Preexisting Neutralizing Antibodies to Ad5 Attenuate the InnateImmune Response to MRKAd5/HIV. An important observation inthe Step Study was that the presence of Ad5 nAb before vacci-nation resulted in increased postvaccination risk of HIV acqui-sition (4), and thus far, no clear mechanism for this has been

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elucidated (3, 7, 8). We therefore analyzed the in vivo innateimmune responses of vaccinated Ad5 seropositive subjects todetermine if we could identify alternate programs of innate ac-tivation in these individuals. The early termination of the Stepand Phambili studies resulted in the cessation of HVTN 071,limiting the number of subjects we could analyze. Given the

possibility of threshold effects of Ad5 nAb (3, 4), we comparedthe responses between subjects with Ad5 nAb titers ≤ 200 and>200, and thereby identified 306 seropositivity effect genes (302at 24 h, six at 72 h) for which the vaccine-induced responses weremarkedly attenuated (Dataset S1, tab 11). Canonical pathwayenrichment analysis of these genes revealed that induction of

Fig. 1. Systems analysis identifies widespread innate immune activation and cellular trafficking responses response to MRKAd5/HIV vaccination in humans. (A)In vivo PBMC transcriptional responses to vaccination with MRKAd5/HIV [n = 7 Ad5 seronegative individuals, false-discovery rate (FDR) ≤ 10%, absolute averagelog2 fold-change ≥ 0.5]. Genes significantly differentially expressed in response to MRKAd5/HIV vaccination at any time point are annotated and groupedaccording to membership in functional gene modules (21, 64). Each column represents subject-specific log2(fold-changes) compared with prevaccination. Toemphasize regulation patterns, expression fold-changes for each gene are scaled by the maximum observed expression response. Pink intensity indicates up-regulation compared with prevaccination, cyan indicates down-regulation. (B) Functional gene modules significantly differentially expressed in PBMC in responseto vaccination. Each black line represents the average log2(fold change) of all genes in the module for a single subject. Up-regulated modules have values >0,down-regulated modules have values <0. FDR < 10%, |average log2(fold-change)|>0.5. (C) Quantitative RT-PCR validation of the differential expression ofmodule-associated genes identified by microarray analysis. Each line represents the response of one individual (n = 7). (D) Protein-level validation of vaccine-induced cytokine and chemokine differential expression by multiplex analyte analysis. (E) Validation of vaccine-induced cellular fluxes predicted by module-levelanalysis of the PBMC transcriptional responses. *P < 0.05 with Hochberg adjustment from the statistical model assessing change in concentration over time.

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complement pathways, innate immune sensors, and G-proteincoupled receptor signaling was significantly attenuated (DatasetS1, tab 12). This attenuation extended to all modules regulated bythe MRKAd5 vaccine (Fig. 3A), including impaired down-regula-tion of lymphocyte modules and genes preferentially expressed inlymphocytes (Dataset S1, tab 11), suggesting suppression of theacute lymphopenia observed in the Ad5 seronegative subjects (Fig.1E). Direct comparison between regulation of innate immunenetworks in seronegative and Ad5 nAb >200 subjects revealedcoordinate dysregulation that included the RIG-I, NLR/inflam-masome, and TLR pathways (visualized using Cytoscape in Fig.3B). Finally, we validated these transcriptional results at the pro-tein level by analyzing serum analytes from a larger set of vacci-nated subjects (Fig. S2). Consistent with the transcriptional results,cytokine responses were markedly attenuated in Ad5 nAb >200subjects compared with Ad5 nAb ≤ 200 subjects (Fig. 3C andDataset S1, tab 13). Taken together, these results suggest that thepredominant effect of preexisting Ad5 nAb on the innate immuneresponse is global attenuation. These data do not support thehypothesis that preexisting immunity leads to enhanced systemicinnate immune activation.

MRKAd5/HIV Innate Immune Responses Predict Immunogenicity. Wenext identified MRKAd5/HIV-induced innate immune sig-natures that predict subsequent HIV-specific adaptive immuneresponses. Based on the frequency of Gag-specific CD8+ T-cellresponses detected at day 28 after one immunization (Fig. S3),we categorized vaccine recipients (n = 31) into high, moderate,or low responders. We determined whether fold-changes in serum

cytokine concentrations, measured 24 h postvaccination (Fig. 1Dand Dataset S1, tab 6), could predict the Gag-specific CD8+ T-cell response magnitudes. We performed two analyses: (i) dis-crimination between subjects with detectible (CD8pos = CD8mod

and CD8high) and undetectable (CD8neg) responses; and (ii) dis-crimination between subjects with high (CD8high) and moderateor undetectable (CD8mod, CD8neg) responses. The predictivepotential of individual cytokines and all cytokine pairs was eval-uated by 60 iterations of eightfold cross-validation of linear dis-criminant analysis (LDA) classifiers.Two chemokines, MCP-1 and MCP-2 (Fig. S4 A and B), dis-

criminated between CD8mod/CD8high subjects and CD8neg subjectswith high accuracy (81% and 88%, respectively), and thus werequalitatively predictive of the vaccine CD8+ T-cell immunoge-nicity. In both cases, higher chemokine induction predicted in-creased likelihood of positive CD8+ T-cell responses. CombiningMCP-1 and MCP-2 into a single classifier did not increase pre-dictive accuracy. However, the accuracy was increased by combi-nation with other cytokines that were not individually predictive(Fig. 4A and Fig. S4A). For example, the growth factor PDGF-AAwas 71% predictive individually but 85% predictive in combina-tion with MCP-1. The network of predictive pairwise signaturesfor CD8+ T-cell responses is shown in Fig. 4A, and the receiveroperating characteristic (ROC) for predicting positive CD8+ T-cell responses based on GRO and MCP-2 is shown in Fig. 4B.Classifiers performing as well as MCP-2 individually (or top pairsinvolving MCP-2) were generated only 13% of the time when theanalysis was repeated on randomized datasets, indicating that theresult is moderately robust. Nevertheless, repeat analyses using

Fig. 2. Responses to MRKAd5/HIV are recapitulated in vitro and involve coordinate regulation of an innate immune network involving unique gene isoforms. (Aand B) In vitro responses of modules regulated byMRKAd5/HIV in vivo. Each black line represents the average log2 fold-change of all genes in the module for PBMCderived from separate donors and stimulated in vitro (n = 4); red line indicates average module-level response in vivo. *P ≤ 0.01 comparing module fold-changesobserved in vitro those observed in vivo. (A) Genemodules consistently regulated byMRKAd5 in vivo and in vitro. (B) Genemodules regulated in vivo but not in vitro.(C) Single gene heatmaps showing average exon-level expression responses toMRKAd5/HIV in vivo (n = 7) and in vitro (n = 4). Pink intensity indicates up-regulation,cyan indicates down-regulation. (D) Innate immune response interaction networkof genes consistently induced in response toMRKAd5 in vivo and in vitro, arrangedby representative subcellular localization. Node colors indicate functional module associations; node shapes indicate the mode of differential expression. Red linesindicate protein-protein interactions, gray lines indicate mutual membership in common complexes, and blue edges indicate protein–DNA interactions.

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similar vaccines are required to confirm the association betweenthese chemokines and CD8+ responses. In the second analysis, thecombination of RANTES (regulated upon activation, normal Tcell expressed and secreted) and IL-28A was predictive of CD8+response magnitudes with high accuracy (87%), even thoughneither cytokine was strongly predictive individually (Fig. S4 C andD). Strong down-regulation of RANTES or up-regulation of IL-28A was associated with induction of high magnitude CD8+ T-cellresponses (Fig. S4D). The ROC for predicting high magnitudeCD8+ T-cell responses based on IL-28A and RANTES is shownin Fig. 4C. Repeating the analysis on randomized datasets gen-erated classifiers performing as well as IL-28A and RANTES 25%of the time, indicating that this particular result should be regar-ded as a hypothesis until additional studies have validated the roleof these cytokines in the fine tuning of adenoviral vector CD8+ T-cell immunogenicity.

Using Systems Biology to Generate Additional Hypotheses Regardingthe Immunogenicity of MRKAd5/HIV.To identify additional potentialmechanisms controlling MRKAd5/HIV-induced T-cell responses,we extended our signatures analysis to the transcriptional level.Given our small data sample sizes, it was not possible to imple-ment approaches described above or in previous studies (19, 20),and the results must be regarded as hypothesis-generating untilclinical studies using similar vaccines make validation of the resultspossible. We defined groups of subjects with high-, moderate-, orlow-magnitude CD8+ T-cell responses by 1D clustering of the gag-specific responses. Genes with statistically significant differencesin vaccine-induced transcriptional responses between the high andlow CD8+ groups were then identified through direct comparison.Surprisingly, significant differences between these groups of sub-jects were only identified from the transcriptional responsesmeasured 72 h postvaccination (88 genes were positively associ-ated and 121 genes were negatively associated) (Fig. 5A and B andDataset S1, tab 14), and none of the MRKAd5-responsive mod-ules differed significantly between the groups. Several of the im-plicated genes have clear functional relationships to cytotoxicresponses, including the inhibitory killer cell Ig-like receptorKIR2DL1, the NK-cell activating receptor CLEC2D (28), and theNK-cell signaling adaptor EWS-FLI1–activated transcript 2 (EAT-2) (29) (Fig. 5 A and B). Consistent with this association betweenEAT-2 expression and CD8+ T-cell responses, it was recentlyreported that adenoviral expression of EAT-2 as part of a vaccine

strategy enhanced vaccine-induced T-cell responses (30). Becauseinteraction network analysis of the overall CD8+ T-cell responsegene set itself was found to be uninformative, we investigatedwhether any the gene set members are protein–protein interactionneighbors of genes belonging to MRKAd5 regulated functionalmodules (Fig. 1B). We found that many of the CD8+ T-cell re-sponse associated genes are nearest neighbors of members of the“Cytotoxicity,” “T cells,” and “Lymphoid lineage” modules (Fig.5C), providing additional support for the association betweenthese genes and CD8+ T-cell immunogenicity.

Replication-Incompetent MRKAd5 Induces a Greater Number ofInnate Immune Genes than Does Live-Attenuated YF-17D, but theResponse Is More Transient. Recent studies have suggested thatthe efficacy of live-attenuatedYF-17D, a yellow fever vaccine (31),may result from robust innate immune activation (18, 19, 32). Wetherefore contrasted the transcriptional responses inducedMRKAd5 and published in vivo profiles for YF-17D (19). Al-though theMRKAd5/HIV vaccine induced more than 1,000 genesand repressed a similar number, the YF-17D vaccine only induced181 genes and repressed 10 genes (Fig. 6A). However, the re-sponse to MRKAd5/HIV was rapid and transient, but the re-sponse to YF-17D lagged and was persistent (Fig. 6A). Modularanalysis further illuminated differences between the two vaccines(Fig. 6B). Whereas MRKAd5/HIV induced the “Inflammation,”“Interferon response,” and “Myeloid lineage” modules andinhibited the “Lymphoid lineage,” “T cells,” and “Cytotoxicity”modules (Figs. 1B and 4B), YF-17D vaccination induced onlya subset of the “Interferon response” modules (M1.2 and M3.4)(Fig. 6B).Given that dosage and replication kinetics could likely account

for the gross differences in innate immune activation betweenreplication defective MRKAd5 and live-attenuated YF-17D, weperformed a new set of comparative in vitro experiments to di-rectly contrast responses to the two vaccines, focusing first ondifferences identified in vivo that recapitulated in vitro. Weidentified 43 genes preferentially induced by MRKAd5/HIV invivo that confirmed in vitro (Fig. 6C), including several associ-ated with innate immune responses (IRF1), the complementpathway (C1QB), pathogen recognition (TLR8), the inflamma-some (CASP10, P2RX7), and NK-cell activation [SLAMF7 (33)].This group also included several immunosuppressive factors,including the T-cell inhibiting IDO1 (34), M2-macrophage

Fig. 3. Preexisting Ad5 neutralizing antibodies at-tenuate the MRKAd5/HIV-induced innate immuneresponse in vivo. (A) Effect of Ad5 nAbs on genemodules regulated by MRKAd5/HIV. Black line rep-resents the average fold-change of all genes in themodules, averaged over 8 Ad5 nAb ≤ 200 subjects.Green lines represent the average fold-change of allgenes in the module for the two Ad5 nAb > 200subjects. (B) Attenuated induction of critical innateimmunity pathways in Ad5 nAb > 200 comparedwith Ad5 nAb ≤ 200 subjects. Nodes are coloredaccording to average extent of induction in Ad5nAb ≤ 200 subjects at 24 h (Left) and average extentof response attenuation in Ad5 nAb > 200 subjectscompared with Ad5 nAb ≤ 200 subjects (Right).Edges represent protein–protein interactions be-tween nodes obtained from InnateDB (65). (C)Representative attenuation of MRKAd5/HIV serumcytokine induction in Ad5 nAb > 200 subjects. Se-rum IP-10/CXCL10 concentrations are contrastedbetween Ad5 nAb ≤ 200 (n = 27) and Ad5 nAb > 200(n = 6) individuals. Shading represents the inter-quartile ranges with the 75th percentile shown ontop and the 25th percentile shown below the me-dian line. *P < 0.05 after Hochberg adjustment.

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skewing TF KLF4 (35), macrophage inhibitor PSTPIP2 (36), andthe PD-1 death receptor ligand PDCD1LG2. The preferentialinduction of three transcription factors by MRKAd5, IRF1,KLF4, and STAT5A suggested that these factors may partlyaccount for the PBMC transcriptome induced by MRKAd5. Bymining published ChIP-Seq datasets (37–39), we confirmed thatseveral MRKAd5-specific genes are direct targets of these tran-

scription factors (Fig. 6D), and that these transcription factorspotentially coregulate each other. Although there were no genespreferentially induced by YF-17D in vivo that validated in vitro,we identified a robust gene set, predominantly consisting of

Fig. 4. Vaccine-induced serum cytokine and chemokine responses predict themagnitudes of CD8+ T-cell responses induced by MRKAd5/HIV. (A) Networkdepiction of serum cytokines and chemokines with 24-h vaccine-induced fold-changes that discriminate subjects who develop CD8+ T-cell responses (28 dafter vaccination) from those who do not. Node sizes indicate predictive ac-curacy of the factors individually (percentages inside nodes), node color, andintensity indicate positive (pink) or negative (blue) correlations between in-duction levels of the factor and CD8+ T-cell response magnitudes. The pres-ence of an edge between nodes indicates that the two cytokines incombination have increased predictive accuracy compared with either cyto-kine alone. Edge width is proportional to predictive accuracy of the pair-wisesignature of the connected nodes (red percentages). (B) ROC for predictingwhich subjects will develop CD8+ T-cell responses, based on 24-h vaccine in-duced fold-changes of GRO andMCP-2 in a LDA model. The red line indicatesthe tradeoff in false positive rate required as the true positive rate is in-creased. Prediction accuracies were estimated from over 60 rounds ofeightfold cross-validation. AUC, area under the curve. (C) ROC for predictingwhich subjects will develop high magnitude CD8+ T-cell responses, based on24-h vaccine induced fold-changes of IL-28A and RANTES in a LDA model.Notation is as in B.

Fig. 5. Systems analysis identifies innate immune response genes that areassociated with the immunogenicity of MRKAd5/HIV. (A) The 209 genes with72-h MRKAd5/HIV-induced expression responses that are positively (Upper)or negatively (Lower) associated with the magnitude of MRKAd5/HIV-in-duced CD8+ T-cell responses. Subjects with low and high magnitude CD8+

T-cell responses are on the Left and Right halves of the heatmap, respectively.Gene selection criteria: FDR ≤ 20% and |average log2(fold-change)| ≥ 0.5.Rows are scaled as in Fig. 1A. Pink intensity indicates up-regulation comparedwith prevaccination, cyan indicates down-regulation. (B) Seventy-two hourMRKAd5/HIV-induced expression responses of two representative genes,stratified by the magnitude of the CD8+ T-cell responses observed in the samesubjects. (C) Protein–protein interaction network emphasizing links betweenCD8+ T-cell response-associated genes identified in Fig. 5A (triangles) andconstituents of functional gene modules differentially regulated by MRKAd5/HIV (circles), colored according to module associations.

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members of the “Interferon response”modules (including STAT1,STAT2, IRF7, and IFI27), that was induced by both vaccines invitro and in vivo (Dataset S1, tab 15).To generate hypotheses about differences in innate immune

activation that may result at the actual sites of MRKAd5 or YF-17D vaccination, we also performed a direct comparison betweenthe in vitro responses to the two vaccines, without constrainingthem by the in vivo results. Unexpectedly, the innate activationprofiles of MRKAd5 and YF-17D differed more strongly in vitrothan we had originally observed in vivo, with 349 and 313 genesbeing preferentially induced by MRKAd5 and YF-17D, re-

spectively, compared with 226 genes being robustly induced incommon (Dataset S1, tab 16). Similar differences in the down-regulated gene sets were observed, with 190 and 229 genes beingpreferentially down-regulated by MRKAd5 and YF-17D, re-spectively, compared with 137 genes being down-regulated incommon.MRKAd5 preferentially inducedT-cell chemoattractants(CXCL9/10/11), MHC genes, and T-cell–associated cytokines(IFNG, IL-2, and IL-7) but YF-17D preferentially induced theIFNA family of antiviral cytokines and several neutrophil chemo-kines (IL-8, CXCL2, -3, -5, and -6). Canonical pathway enrichmentanalysis reinforced the differences between the two vaccines, with

Fig. 6. MRKAd5 induces more extensive innate immune activation than the gold-standard yellow fever vaccine, YF-17D. (A) MRKAd5/HIV and YF-17D triggerinnate immune responses in PBMC with distinct kinetics in vivo. The number of genes significantly up-regulated (upper half) or down-regulated (lower half) inresponse to vaccination with MRKAd5/HIV (red, present study) or YF-17D [blue (19)] are plotted. Significant differential expression defined as FDR ≤ 10%, |average[log2(fold-change)]| > 0.5; n = 7 (MRKAd5/HIV), n = 25 (YF-17D). (B) MRKAd5/HIV regulates a broader spectrum of gene modules in vivo than does YF-17D. Each line represents the average fold-change of all genes in a module for a given individual (red lines, MRKAd5/HIV vaccines; blue lines, YF-17Dvaccinees). Modules labeled in red differ significantly between MRKAd5/HIV and YF-17D in vivo (FDR ≤ 10%), modules labeled with asterisks differ signif-icantly between MRKAd5 and YF-17D in vivo and in vitro (FDR ≤ 10%). (C) Average expression responses in vivo and in vitro of 43 genes preferentially inducedby MRKAd5. Genes associated with functional gene modules are indicated. Rows are scaled as in Fig. 1A. Pink intensity indicates up-regulation compared withcontrols, cyan indicates down-regulation. FDR < 10%, |average log2(fold-change)|>0.5 for induction in response to MRKAd5 and comparing MRKAd5 to YF-17D, in vivo and in vitro. (D) Putative transcriptional regulatory network controlling innate immune responses preferentially induced by MRKAd5. Squaresindicate transcription factors preferentially induced by MRKAd5 in vivo and in vitro; circles indicate target genes preferentially induced (pink) or repressed(light blue) by MRKAd5 in vivo and in vitro. Lines indicate protein-DNA transcription factor–target gene interactions identified from published ChIP-seqdatasets [blue, KLF4 targets (38); purple, IRF1 targets (37); orange, STAT5A targets (39)]. Pink edges indicate IRF1 target genes identified by conventionalmethods (66–68). (E) Expression responses of CRIP3 and NPB (72–168 h postvaccination) are negatively associated with CD8+ T-cell response magnitudesinduced by MRKAd5/HIV and YF-17D. Shown are log2(fold-changes) compared with prevaccination of the two genes for both vaccines, stratified by themagnitudes of vaccine-induced CD8+ T-cell responses observed in the same subjects. Lines indicate mean values.

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MRKAd5-specific gene enrichments including “Antigen Pre-sentation Pathway” and “T Helper Cell Differentiation” and YF-17D–specific gene enrichments, including “Systemic Lupus Eryth-ematosus Signaling” and several IL-17 associated pathways (DatasetS1, tab 17). These results indicate that greater specificity in vaccine-induced innate immune responsesmay be revealed by profiling local,rather than systemic responses.Finally, we evaluated whether the transcriptional signatures

associated with enhanced CD8+ T-cell responses induced byMRKAd5/HIV (Fig. 5A) were also associated with enhancedCD8+ T-cell responses to YF-17D, despite the numerous differ-ence between the vaccines. By reanalyzing published YF-17Dtranscriptome and longitudinal CD8+ T-cell response data (19)using the approach implemented above, we identified two genes,CRIP3 and NPB, with vaccine-induced expression responses thatwere consistently associated with impaired CD8+ T-cell responsesto both vaccines (Fig. 6E). Strengthening the associations, theaverage fold-changes for these genes formoderate CD8+ responsesubjects was always between that of high and low CD8+ responsesubjects, even though the data for the moderate subjects was notused in the gene selection.Taking these data together, we have defined the early innate

immune response to the MRKAd5/HIV vaccine, identified anattenuated innate response in individuals with Ad5 nAb, anddefined innate response signatures that predict CD8+ T-cellresponses to Gag. These data suggest previously unexploredtargets for enhancing the immunogenicity of next-generationHIV vaccines.

DiscussionSystems biology analysis can contribute to rational vaccine designin four major ways. First, it can enable the identification of cor-relates of immunogenicity and protection; second, it can reveal theregulatory networks within cells that lead to the desired host im-mune response; third, it can guide the reengineering of the vaccineregimen to favor desirable responses; and finally, it can supplytools to glean insight from failed candidate vaccines. We believethis study provides fresh understanding in each of these ways to thehighly immunogenic but nonefficacious MRKAd5/HIV vaccine.Despite inducing T-cell responses at a high frequency,

MRKAd5/HIV neither reduced HIV-1 acquisition nor loweredviral loads postacquisition in two independent clinical trials (3, 5).Furthermore, Ad5 seropositive male vaccine recipients in the Stepstudy showed an increased rate of HIV-1 acquisition, making theinfluence of Ad5 nAbs on vaccine responses an area of intenseresearch (3, 4, 7, 8, 40–42). Although additional factors likelyplayed a role in acquisition (43–45), the effect of Ad5 nAbs wassignificant and has been supported in the nonhuman primate SIVchallenge model. One current hypothesis is that antibody-medi-ated internalization of Ad5 results in increased dendritic cell ac-tivation, which may lead to enhancedHIV-1 infectivity (40). In ourstudy, we found no evidence for enhanced or prolonged systemicinnate immune responses in volunteers with preexisting Ad5 nAb.Instead, we observed attenuation of the overall transcriptionalresponse (Fig. 3 A–C), which we confirmed at the protein level bymultiplex serum cytokine analysis (Fig. 3D andDataset S1, tab 13).Our results are compatible with the suggestion that Ad5 nAb mayeffectively lower the dose of the vaccine detected by the innateimmune system (8, 46) and are consistent with the reduced vaccineimmunogenicity seen in vaccine recipients with nAb titers >200(3). Our results are also compatible with a model in which nAbsnegatively regulate innate signaling pathways. The latter hypoth-esis is of interest given the possibility that the opsonized vectorcould interact with Fc receptors on antigen presenting cells; anevent that might result in an inappropriate context for pre-sentation of the vaccine-encoded antigens. Regardless of theprecise mechanism, our observations highlight the impact of pre-existing type-specific immunity to the vector on vaccine responsesand open new avenues for mechanistic studies into the effects ofthis important variable.

Few vaccine vectors in development match Ad5 in terms of themagnitude and frequency of vaccine insert-specific CD8+ T cellsthey induce (Fig. S3) (3). Ad5-induced CD8+ T cells are func-tional in some settings, because they are essential to the efficacyof Ad5-vectored Ebola vaccines in the nonhuman primate model(10) and also appear to have exerted selective pressure oninfecting HIV-1 in the Step Study (6). Results in the murinemodel, however, show that Ad5 induced CD8+ T cells may notproperly differentiate into memory cells required for protectiveresponses.† These contrasting results suggest that although thestrong Ad5-induced CD8+ T-cell response may be sufficient forvaccine efficacy in some systems, increases in the efficacy of Ad5-based vaccines may be achieved if the quality of the inducedCD8+ T cells is optimized.To determine how the magnitude and quality of vaccine-in-

duced T-cell responses are shaped and may ultimately be opti-mized by activation of innate pathways, we performed twohypothesis-generating analyses. First, we evaluated innate im-mune response signatures that were associated with vaccine-in-duced CD8+ T-cell magnitude, and second, we compared itsinnate activation profile with that of the highly efficacious yellowfever vaccine YF-17D.In the signature analyses, we found that serum induction of the

two chemokines, MCP-2 and MCP-1, 24 h postvaccination,predicted whether or not a subject would develop a measureableCD8+ T-cell response 4 wk postvaccination (Fig. 4 A and B, andFig. S4 A and B). Predictive accuracy was increased to nearly90% by coupling these chemokines with proinflammatory cyto-kines (Fig. 4 A and B, and Fig. S4 A and B). Although additionalstudies are required to confirm this result, a role for these che-mokines in CD8+ T-cell responses is supported by the strong T-cell chemoattractant function they exhibit (47) and the reportedCD8+ T-cell adjuvant activity of MCP-1 (48). Furthermore,there was an indication in our data that subjects with the highestCD8+ T-cell responses were those who either strongly down-regulated RANTES or up-regulated IL-28A (Fig. 4C,and Fig. S4C and D). One hypothesis is that strong down-regulation of se-rum RANTES postvaccination may indicate increased uptake bymigrating inflammatory cells, but increased serum IL-28A mayindicate an immunogenic role for the antiviral activities of thiscytokine (49, 50). The transcriptional CD8+ signature analysisalso revealed many genes exhibiting responses to MRKAd5/HIVat the 72-h timepoint that were significantly associated withCD8+ T-cell response magnitudes (Fig. 5 A and B), includingseveral that are nearest neighbors of CD8+ T-cell response-as-sociated module genes (Fig. 5C). One compelling component ofthe gene signature was EAT-2 (Fig. 5B), which was recentlyreported to enhance the frequency of vaccine induced T cellswhen encoded in an Ad5 vector (30). Despite the striking dif-ferences in innate response kinetics between the vaccines, wealso tested whether the CD8+ signature for MRKAd5/HIV wasassociated with CD8+ T-cell response magnitudes for YF-17D.Reanalysis of the published YF-17D dataset (19) identified twogenes, CRIP3 and NPB, with induction patterns that were asso-ciated with the CD8+ T-cell responses of both MRKAd5/HIVand YF-17D (Fig. 6E). Roles for both of these genes in vaccinemechanisms are plausible, given the function of CRIP3 in thymiccellularity (51) and the high expression levels of NPB in lym-phoid tissues (52).In the comparative analysis, we found a striking difference in

the temporal innate immune activation profile of MRKAd5/HIVand YF-17D (Fig. 6A) that is consistent with, but not completelyexplained by, the dosage and pharmacokinetics of the vaccines:although replication-incompetent MRKAd5/HIV is present atthe highest levels immediately after injection (53), live-attenu-ated YF-17D takes 5–7 d to reach maximal titers in the host (31).Unexpectedly, the innate immune response to MRKAd5/HIV

†Sarkar S, et al, Keystone Symposia on Molecular and Cellular Biology, October 27–November 1, 2010, Seattle, WA.

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was much more extensive than that induced by YF-17D (Fig. 6 Aand B). Although the peak response to MRKAd5/HIV involvedinduction of over a dozen functional modules, the peak responseto YF-17D involved induction of only two. In vitro stimulationexperiments with the two vaccines identified which of the innateimmune response differences observed in vivo are because ofcell-intrinsic differences in innate immune signaling (Fig. 6 C andD). MRKAd5 preferentially induced a transcriptional regulatorynetwork involving three transcription factors, IRF1, KLF4, andSTAT5A, in vivo and in vitro (Fig. 6 C and D). Activation of theIRF1 network may play a part in the strong CD8+ T-cell immu-nogenicity of MRKAd5/HIV, given the role of this transcriptionfactor in regulating MHC class I presentation and CD8+ T-cellresponses (54). Interestingly, a number of the MRKAd5-specificgenes are also associated with immunoregulatory functions.Among these, KLF4 promotes anti-inflammatory “M2” andinhibits proinflammatory “M1” macrophage polarization (35),and PDCD1LG2 and IDO1 suppress T-cell activation througha variety of mechanisms (55, 56). Further study will determinewhether pharmacological inhibition of these molecules will leadto enhanced Ad5-induced T-cell functionality. Finally, directcomparison between MRKAd5- and YF-17D–induced innate im-mune responses in vitro revealed additional functionally relevantdifferences between the vaccines, suggesting that profiling of localresponses may complement measurements of systemic responsesobtained by from blood cell transcriptomes.Our comprehensive analysis of the immediate systemic re-

sponse following vaccination with MRKAd5 provides fresh un-derstanding of vaccine-induced innate immune activation, how itis modulated by preexisting immunity, and how it relates to thesubsequent adaptive immune responses. Such understanding willplay an important role in the development of a highly efficaciousHIV vaccine.

Materials and MethodsSubjects. We enrolled 35 healthy HIV-1-uninfected adults [median age 37 y(range 20–50); 21 female; 28 Caucasian, 7 African American]. Eleven subjectswere Ad5Positive and 24 were Ad5Neg (Fig. S2). Microarrays were run on fivemales and five females [median age 33 y (range 22–43); nine Caucasians].Female participants were counseled to use birth control and avoid preg-nancy during the study. All participants provided written informed consent,and each of the four United States trial sites obtained approval for the studythrough their institutional review boards.

Study Design. HVTN 071 was a Phase 1b multicenter, open-label trial(ClinicalTrials.gov #NCT00486408). At the start of the trial (day 0), all volunteerswere intramuscularly vaccinated with 1.5 × 1010 genomes of the previously-described MRKAd5/HIV vaccine (3); 24 received a second vaccination at day 28before all MRKAd5/HIV vaccinations were suspended (4). Blood was collectedimmediately before vaccination and at 4–6, 24, 72, and 168 h postvaccinationfor 11 individuals. Serumwas obtained from an additional 24 individuals at theprevaccination and 24-h time points.

Microarrays and Quantitative Real-Time PCR. PBMC were isolated from bloodas previously described (57). RNA was extracted from PBMC using the RNeasyProtect Cell protocol (Qiagen). Before labeling, the integrity of samples waschecked using an Agilent 2100 Bioanalyzer.

Affymetrix Exon Arrays. RNA expression for the in vivo study and one in vitrostudy was analyzed using the Human Exon ST 1.0 microarray platform (Affy-metrix) essentially as described in ref. 17. For in vivo profiling, 50 samples wereanalyzed: five time points (prevaccination and 6, 24, 72 and 168 h post-

vaccination) for 10 subjects (three Ad5-seropositive and seven Ad5-seroneg-ative). For in vitro profiling, eight samples were analyzed: PBMC obtainedfrom four Ad5 seronegative donors stimulated for 24 h with MRKAd5 emptyvector at 20,000 particles per cell and GTS buffer mock control.

Agilent 3′Arrays. RNA from theMRKAd5 vs. YF-17D comparative in vitro studywas analyzed using the Agilent SurePrint G3 Human GE 8 × 60K microarrayplatform (Agilent Technologies), essentially as described in ref. 17. Forcomparative in vitro profiling, 16 samples were analyzed: PBMC obtainedfrom four Ad5 seronegative donors stimulated for 24 h with MRKAd5 emptyvector at 60,000 particles per cell and GTS buffer mock control or YF-17D at30 particles per cell and DMEM 2% (vol/vol) FCS buffer mock control.Microarray data analysis procedures are described in the SI Materials andMethods. Quantitative real-time PCR was performed as described in ref. 17.

Multiplex Cytokine Analysis. Serum cytokine analysis was performed using theLincoplex High Sensitivity kit (Millipore Cat# HSCYTO-60SPMX13) and regularsensitivity kits (Millipore Cat# MPXHCYTO60KPMX42, MPXHCYP2:00 PMX23,and MPXHCYP3-PMX9), according to the manufacturer’s instructions (Linco/Millipore), and samples were analyzed on a Luminex 200 (Luminex). PBMCsupernatants were assayed similarly for a subset of the analytes. Data wereanalyzed using a custom in-house export and quality control program inconjunction with the Ruminex program (58).

Enumeration and Phenotyping of Fresh Blood Cell Populations. Trucount tubes(BD) were stained with CD45-ΑPC, CD14-PE, CD3-PerCp, and CD8-FITC (allfrom BD). For further phenotyping, whole blood was diluted 1:10 in Pharm-lyse RBC lysis buffer (BD), incubated 10 min at room temperature andcentrifuged at 750 × g for 5 min. RBC lysis was repeated and cells wereresuspended in cold PBS; 2 × 106 to 6 × 106 cells were stained with Aqua Vi-ability Dye (Invitrogen), followed by one of three antibody mixtures (detailsprovided upon request). Cells were fixed with PBS containing 1% para-formaldehyde and stored at 4 °C until analysis by flow cytometry. All samplesfrom one volunteer were analyzed together within 7 d of staining.

Statistical Analysis of Cell Concentration and Multiplex Cytokine Data. Analysisof analytes altered after vaccination was performed by running a mixedmodel with normally distributed errors and an unstructured covariancematrix, with cytokine or cell concentration as the dependent variable andcategorical sampling time as the independent variable, allowing randomintercepts for each participant for each immunization series and each cy-tokine or cell type. Sex and age were included as possible confounders. Pvalues for time were adjusted within a given vaccine series using theHochberg method (59). Methods for identification of serum analyte profilesthat were predictive of CD8+ T-cell responses are provided in the SI Materialsand Methods.

In Vitro PBMC Stimulations. One-million PBMC fromhealthy Ad5-seronegativeindividuals were stimulated with MRKAd5 empty vector or GTS buffer mockcontrol (60) or YF-17D or DMEMwith 2% (vol/vol) FCS mock control [courtesyof Charles Rice, Rockefeller University, New York (61–63)] in RPMI containing10% (vol/vol) FCS, penicillin and streptomycin at a range of multiplicities ofinfection. After 24 h, cell-culture supernatants were harvested for multiplexcytokine analysis and cells were frozen in RLT buffer (Qiagen) containingβ-mercaptoethanol, for RNA purification and microarray analysis.

ACKNOWLEDGMENTS. We thank the HVTN 071 Protocol Team, MichaelRobertson, Youyi Fong, Greg Spies, Jennifer Vogt, Jim Simandl, Don Carter,Stephen Voght, Lamar Fleming, Marcus Altfeld, and Galit Alter for theirassistance, and the James B. Pendleton Charitable Trust for their generousequipment donation. This work was supported by National Institutes of HealthGrants UM1 AI068618 and U01 AI069481 (to M.J.M.); the Bill and MelindaGates Foundation Collaboration for AIDS Vaccine Discovery Grant 38645 (toM.J.M.); and National Institutes of Health Grant T32 AI007140 (to E.A.-N.).

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